The Internet is being increasingly used to search for and view images (e.g., photographs). To support this use, commercial search engine services have located and indexed over 1 billion images since 2005. Users who search for images often want to locate and view images that are either photographs or graphics. Photographs (e.g., portraits) are a class of images typically acquired by cameras and scanners, and graphics (e.g., chart or drawing) are a class of images generated by computers. A person searching for images may know the semantic content and the class of image of interest. For example, a person may want to locate a cartoon that contains a picture of a dog. After submitting an image query such as “dog cartoon,” the user may be presented with hundreds of images as the search result and needs to review all the images to identify those images of the desired class. It would be helpful if the user could limit the search to only graphic images when searching for images generated by a computer.
Current commercial image search engines, however, do not allow a user to limit a search to photographic or graphic images. These search engines typically locate images of web pages based on text such as text surrounding the image or text of a file name or images of image forums based on text of metadata such as description, file name, and reviewer comments. This text may describe the semantic content of an image (e.g., “dogimage1.jpg”) to a certain extent, but rarely classifies the image as being a photograph or graphic.
The classifying of images as a photograph or graphic is also useful in personal image management. A person may have thousands of images stored on their computer system and may want to search only for photographic images or only for graphic images. For example, a person may want to view only their personal photographs or may want to view only their collection of business graphics. Also, when automatically processing images, it can be important to distinguish photographs from graphics. For example, a person may want to add a border to all the photographs, but not to graphics.
Current techniques for classifying images as photographs or graphics are either inaccurate or computationally expensive. One technique tends to differentiate photographs from graphics based on various features of the images including the number of colors, most prevalent color, a farthest neighbor metric, and a saturation metric. Such a technique, however, has a relatively high error rate. Another technique uses image geometry to differentiate photographs from graphics. This technique, however, can take more than 50 seconds to classify an image, which makes the technique impractical for use in web-based image searching.